摘要
为了提高恒虚警检测器在多目标环境下的检测性能及有效控制杂波边缘环境中虚警率的上升,基于结合高效的无偏最小方差估计(UMVE)算法提出了一种新的最大选择恒虚警检测算法(OSUMGO-CFAR),它的前、后沿滑窗分别采用OS和UMVE方法得到两个局部估计,将其中的最大值作为背景杂波功率水平估计,去设置自适应检测门限。在SwerlingⅡ型目标假设下,推导了该算法在均匀背景下的矩产生函数MGF、平均判决阈值ADT、多目标环境下检测概率Pd和杂波边缘环境中虚警尖峰的数学解析表达式。采用数值计算的方法,将恒虚警损失及虚警尖峰分别作为衡量算法在多目标和杂波边缘环境下性能优劣的标准。分析结果表明,该算法在多目标和杂波边缘引起的非均匀背景中的性能,均比OSTMGO和GOSGO算法得到了改善。
In order to improve the detection performance of constant false alarm detectors in multi - targets environment and effectively control the rise of false alarm rate at the clutter edges, a new CFAR detecting algorithm （ OS- UMGO- CFAR） is proposed based on efficient unbiased minimum- variance estimation （UMVE）. In this algorithm, OS and UMVE methods are respectively adopted to create two local noise power estimations, the maximum value of them is used to set an adaptive detection threshold. Under Swerling Ⅱ assumption, the analytic expressions of MCF and ADT in homogeneous background are derived , again the analytic expressions of Pd in multi - targets environment and the peak of false alarm rate at clutter edges are derived. With numerical analysis, the CFAR - LOSS and peak of false alarm rate are taken respectively as the measurement of performance in multi - targets environment and at the clutter edges. The analysis results show that the algorithm is better than OSTMGO and GOSGO in performance in non -homogeneous background.
出处
《空军工程大学学报（自然科学版）》
CSCD
北大核心
2008年第5期38-42,共5页
Journal of Air Force Engineering University(Natural Science Edition)
基金
国家"863"计划资助项目(2006AAX01XXX)
关键词
检测
恒虚警
无偏最小方差估计
虚警尖峰
detection
constant false alarm rate （CFAR）
unbiased minimum- variance estimation
peak of false alarm rate
